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Genetic Interpretation System for Screening Monogenic Disorders Carriers

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Health Information Science (HIS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12435))

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Abstract

Monogenic disorders are remained a common issue in some countries due to poor environmental factors and unnecessary mutations, more specifically in the rural areas, the monogenic disorder ratio is much more higher because of the consanguineous marriages. According to the OMIM database, there are currently more than 8,000 single-gene diseases identified. Although monogenic diseases are rare, the overall incidence is nearly 1/100. Among various birth defects, the proportion of single gene diseases is as high as \(22.2\%\). Among neonatal deaths, \(20\%\) of them are caused by recessive genetic diseases, and \(80\%\) of patients with recessive genetic diseases have no family genetic history. Screening of carriers of single-gene inherited diseases based on specific populations has been proposed since the 1970s, however the cost was very high and it was impossible to be widely used. In the past few years, with the fast development of genetic testing technology and clinical applications, more and more single-gene associated diseases have been discovered, and the cost for screening monogenic disorders has become less and less. In this paper we first introduce the single-gene inherited diseases, then we explain how to identify the single-gene inherited diseases, finally we describe the working mechanism and implementation of the genetic interpretation system for screening monogenic disorders carriers.

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Acknowledgment

This work was partially supported by the Science Foundation of Beijing Language and Culture University (supported by “the Fundamental Research Funds for the Central Universities”) (20YJ040007, 19YJ040010, 17YJ0302).

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Correspondence to Jitao Yang .

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Yang, J., Li, B. (2020). Genetic Interpretation System for Screening Monogenic Disorders Carriers. In: Huang, Z., Siuly, S., Wang, H., Zhou, R., Zhang, Y. (eds) Health Information Science. HIS 2020. Lecture Notes in Computer Science(), vol 12435. Springer, Cham. https://doi.org/10.1007/978-3-030-61951-0_11

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  • DOI: https://doi.org/10.1007/978-3-030-61951-0_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61950-3

  • Online ISBN: 978-3-030-61951-0

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